Timescale: Oct. 2018 – March 2022
PD Dr. Heidi Kreibich, GFZ Potsdam
PD Dr. Gert Zöller, University of Potsdam
Losses from floods have dramatically increased during the last few decades and losses of companies have a large share of the total economic losses. This observed increase in flood losses is dominated by exposure increase, while an impact of changes in flood hazard due to anthropogenic climate change has hardly been observed to date (Bouwer, 2011; Merz et al., 2012). The climate signal might be masked by a counteracting decrease in vulnerability. However, knowledge about temporal trends in vulnerability and the role of vulnerability for changes in flood risk is largely lacking (Mechler and Bouwer, 2015). The vulnerability may be positively influenced by flood risk management and other formal measures like land use planning, but it can also be negatively influenced by changes in business processes, like increasing global economic relations and just-in-time production.
This project extensively analyses past changes in vulnerability in respect to flood induced business interruption. First, the effect of the most important variables determining duration and resulting costs of flood induced business interruption will be quantified; second: potential temporal changes in business interruption will be analysed (detection of change); thirdly: the main drivers of change will be identified (attribution). The innovative aspect is that the temporal dynamic of damage processes leading to business interruption will be analysed using data-mining methods. Thus, the project contributes to analysing, i.e. detecting and attributing changes in flood risk due to global change, particularly related to economic and technological changes.
As such, the project supports the overall objective of NatRiskChange in developing and applying data mining methods like decision trees or Bayesian networks to assess and quantify the non-stationarity of flood risk, as a result of changes in technical vulnerability. It contributes to achieve the key scientific aim of developing, testing, and applying methods to identify processes associated with transient flood risk.
Objectives and Methods
This project will analyse past changes in vulnerability in respect to flood induced business interruption and will identify the main drivers of change. It contributes to the over-arching goal of quantifying processes associated with transient flood risk.
The key research questions focussed on single companies are:
In this project “data analyses methods” as well as “Bayesian approaches” will be applied. Flood vulnerability data, collected via computer aided telephone interviews with flood-endangered companies after all large damaging floods in Germany since 2002, will be analysed with multivariate statistical methods including data-mining. For instance, Bayesian networks, decision trees or complex networks may be used to analyse the complex interactions of variables that influence time and costs of flood induced business interruption. If long enough time series data are available, also methods of time series analysis (e.g. decomposition) will be applied to analyse trends of variables (e.g. economic indicators) changing the vulnerability of companies.
Publications within NatRiskChange:
BERGHÄUSER, L., SCHOPPA, L., ULRICH, J., Dillenardt, L., Jurado, O.E., PASSOW, Ch., Mohor, G.S., Seleem, O., Petrow, Th., Thieken, A.H. (2021): Starkregen in Berlin: Meteorologische Ereignisrekonstruktion und Betroffenenbefragung, Bericht, 73 Seiten, Universitätsverlag der Universität Potsdam, doi: https://doi.org/10.25932/publishup-50056
SCHOPPA, L., Kreibich H., Sieg T., Vogel K. and Zöller G. (2021): Developing multivariable probabilistic flood loss models for companies [Paper presentation]. FLOODrisk 2020 - 4th European Conference on Flood Risk Management, Online-Conference. https://doi.org/10.3311/floodrisk2020.11.12
SCHOPPA, L., Disse, M., & Bachmair, S. (2020): Evaluating the Performance of Random Forest for Large-Scale Flood Discharge Simulation. Journal of Hydrology, 125531, https://doi.org/10.1016/j.jhydrol.2020.125531.
SCHOPPA, L., Sieg, T., Vogel, K., Zöller, G., Kreibich, H. (2020): Probabilistic Flood Loss Models for Companies. Water Resources Research, 56, 9, e2020WR027649, https://doi.org/10.1029/2020WR027649.